pandas.DataFrame.explode

DataFrame.explode(column, ignore_index=False)

Transform each element of a list-like to a row, replicating index values.

New in version 0.25.0.

Parameters

columnstr or tuple

Column to explode.

ignore_indexbool, default False

If True, the resulting index will be labeled 0, 1, …, n - 1.

New in version 1.1.0.

Returns

DataFrame

Exploded lists to rows of the subset columns; index will be duplicated for these rows.

Raises

ValueError :

if columns of the frame are not unique.

See also

DataFrame.unstack

Pivot a level of the (necessarily hierarchical) index labels.

DataFrame.melt

Unpivot a DataFrame from wide format to long format.

Series.explode

Explode a DataFrame from list-like columns to long format.

Notes

This routine will explode list-likes including lists, tuples, sets, Series, and np.ndarray. The result dtype of the subset rows will be object. Scalars will be returned unchanged, and empty list-likes will result in a np.nan for that row. In addition, the ordering of rows in the output will be non-deterministic when exploding sets.

Examples

>>> df = pd.DataFrame({'A': [[1, 2, 3], 'foo', [], [3, 4]], 'B': 1})
>>> df
           A  B
0  [1, 2, 3]  1
1        foo  1
2         []  1
3     [3, 4]  1

>>> df.explode('A')
     A  B
0    1  1
0    2  1
0    3  1
1  foo  1
2  NaN  1
3    3  1
3    4  1

pandas.DataFrame.expanding pandas.DataFrame.ffill